[ECCV 2020] Learning Enriched Features for Real Image Restoration and Enhancement. SOTA results for image denoising, super-resolution, and image enhancement.
In every MRB, features are downsampled, and the feed into DAU. It is obvious that DAU don't change features shape, so the input to SKFF will have different shape and channel. How can SKFF handle these features by simply using L=L_1+L_2+L_3?
In every MRB, features are downsampled, and the feed into DAU. It is obvious that DAU don't change features shape, so the input to SKFF will have different shape and channel. How can SKFF handle these features by simply using
L=L_1+L_2+L_3
?